A wavelet based method for electrical stimulation artifacts removal in electromyogram

International audienceA technique for artifact removal based on the continuous wavelet transform is presented. It uses common mother wavelets to find the temporal localization of stimulation artifacts on electromyogram signal recording during an electrical surface evoked contraction of a muscle. This method is applied with different kinds of stimulation pulse parameters including shape and duration changes. This method is used with standard stimulation pulse waveforms such as monophasic or biphasic ones. It can also be applied when the artifacts and M waves are in the same range of amplitude where threshold techniques are inefficient. Lastly, a method to determine which mother wavelet efficiently removed artifacts is proposed, results indicate the Haar wavelet performs best among fourteen tested wavelets

Classification of Cardiac Arrhythmia in vitro based on Multivariate Complexity Analysis

International audienceBackground: The animal models (in vitro or in vivo) provide an excel-lent tool to study heart diseases, among them the arrhythmia remains one of the most active research subjects. It can be induced or treated by drugs, electrical stimulation, hypothermia etc.Problems: However, the inducing or treating effects in cardiac culture often happened long after the initial applications or in some relatively short time windows. So, it is necessary to capture and classify rapidly the signal change. Human-assisted monitoring is time-consuming and less efficient. An automatic classification method for real-time use would be useful and necessary. Methods: Since electrocardiological signals are features by repetitive or similar patterns reflecting the intrinsic information about the pa-tient (or culture), analyzing these patterns could help not only to monitor the status's change but also to evaluate/explore the physiol-ogic control mechanisms. Methods based on complexity analysis are of considerable interest in this case. Aims: Compare different complexity analysis methods in order to find the most appropriate ones to discriminate the normal cardiac signals from arrhythmic ones acquired from a cardiac cell culture in vitro. The selected features are then used by a SVM classifier.Results: Among the six complexity analysis methods, Time Lagging (TLag) method allowed obtaining the best discrimination index (nor-mal vs. arrhythmic, p-value, 9e-23). The proposed Modified Hurst Exponent (HExM) showed better performance than original Hurst Exponent with well-improved p-value (from 0.019 to 2e-9). The Ap-proximate Entropy (ApEn), Sample Entropy (SampEn) and Detrended Fluctuation Analysis gave good discrimination ratio but with larger p-values (at order 10^{-3}). Combination of TLag, HExM and ApEn can provide a more robust classifier and allow monitoring and classifying in an automatic way the electrical activities' changes in the cardiac cultures

Analyse et détection des électrogrammes complexes fractionnés en vue de soigner la fibrillation auriculaire à l'aide de techniques d'ablation par radiofréquence

Ce manuscrit présente des travaux de recherche sur l analyse et la détection des Electrogrammes Auriculaires Complexes Fractionnés (EACF). Dans une première partie faisant suite à une présentation des mécanismes et des signaux bioélelectriques de la Fibrillation Auriculaire (FA), les outils les plus couramment utilisés pour l analyse des signaux EACF sont présentés. Des outils linéaires sont dans un premier temps appliqués aux signaux intracardiaques issus des procédures d ablation de la FA par radiofréquence puis des outilsnon linéaires sont présentés et intégrés à un algorithme de détection des EACF. Ce dernier s appuie sur la quantification des propriétés de récurrence des électrogrammes. Dans la seconde partie, la cellule et le tissu musculaire cardiaque sont détaillés puis simulés à l aide de plusieurs modèles mathématiques. Ceux de FitzHugh Nagumo, Aliev Panfilov et Courtemanche Ramirez Nattel sont mis en oeuvre afin de reproduire les mécanismes de la FA évoqués dans la présentation de cette pathologie. L acquisition des champs de potentiels est également reproduite à l aide d un modèle numérique de cathéter tel que celui utilisé lors des procédures. Les signaux temporels ainsi générés permettent de lier les activations spatiotemporelles au niveau du substrat aux motifs observables dans les EACF. Un modèle expérimental vient compléter la partie modélisation. Les cultures de cellules de rats nouveaux nés sur puces MEA (Micro Electrode Array) permettent de recréer des conditions de fibrillation et d acquérir des potentiels extracellulaires. Là encore, les électrogrammes sont comparés aux signaux issus des simulations numériques ainsi qu aux signaux cliniques. L analyse des séquences de motifs via les trois types de modèles utilisés permet de rattacher les motifs observés dans les électrogrammes aux mécanismes se produisant au niveau du tissu cardiaque lors de la FA. Une analyse en temps réel permettrait de fournir au praticien des informations déterminantes lors de l ablation concernant la nature et la localisation des sources d arythmieThis manuscript presents research on the analysis and the detection of Complex Fractionated Atrial Electrograms (CFAE). In the first part, following a presentation over Atrial Fibrillation (AF) mechanisms and bioelectrical signals, the most commonly used tools for analyzing CFAE are presented. Linear tools are initially applied to signals from AF ablation procedures, then nonlinear tools are shown and integrated intoa CFAE detection algorithm. This one is based on the quantification of electrogram recurrence properties. In the second part, the cell and cardiac muscle tissue are described and simulated using mathematical models. Models such as FitzHugh Nagumo, Aliev Panfilov and Courtemanche Ramirez Nattel are implemented to reproduce the mechanisms of AF mentioned in the presentation of this disease. The acquisition of fields of potential is also reproduced using a numerical model of catheter as the one used during ablation process. Time signals thus generated are used to match the spatiotemporal activations at the substrate level with the patterns to be observed in CFAE. An experimental model completes the analysis. Cell cultures of newborn rats on MEA (Micro ElectrodeArray) can recreate fibrillation conditions and acquire extracellular potentials. Again, electrogramsare compared with signals from computer simulations and the clinical database signals. The analysisof pattern sequence via the three types of models can attach the observed patterns in electrograms with the mechanisms occurring at the cardiac tissue level during AF. Real-time analysis would allow the practitioner to receive critical information during ablation about the nature and the location of arrhythmia sourcesDIJON-BU Doc.électronique (212319901) / SudocSudocFranceF

Complexity analysis of experimental cardiac arrhythmia

International audienceTo study the cardiac arrhythmia, an in vitro experimental model and Multielectrodes Array (MEA) are used. This platform serves as an intermediary of the electrical activities of cardiac cells and the signal processing / dynamics analysis. Through it the extracellular potential of cardiac cells is acquired, allowing a real-time monitoring / analyzing. Since MEA has 60 electrodes / channels dispatched in a rectangular region, it allows real-time monitoring and signal acquisition on multiple sites. The in vitro experimental model (cardiomyocytes cultures from new-born rats' heart) is directly prepared on the MEA. This carefully prepared culture has similar parameters as cell of human's heart. In order to discriminate the cardiac arrhythmia, complexity analysis methods (Approximate Entropy, ApEn and Sample Entropy, SampEn) are used especially taking into account noise. The results showed that, in case of arrhythmia, the ApEn and SampEn are reduced to about 50\% of the original entropies. Both parameters could be used as factors to discriminate arrhythmia. Moreover, from a point of view of biophysics this decrease 50\% of Entropy coincides with the bifurcation (periods, attractors etc.) in case of arrhythmia which have been reported previously. It supports once more the hypothesis that in case of cardiac arrhythmia, the heart entered into chaos which helps to better understand the mechanism of atrial fibrillation

On the feasibility of movement detection from portable, cost effective, dry EEG headset

International audienceOn the feasibility of movement detection from portable, cost effective, dry EEG headse

Narrowband digital filtering with random frequency hopping spread spectrum

International audienceIn digital signal filtering, channels with narrow bandwidth need high order digital filter to be selected without introducing modulation errors. If a carrier randomly switches from a channel to another as in military applications, or some civilian communication standards, it is necessary to detect and estimate these jumps before transposing and analyzing signals in the baseband. This paper presents a real time solution to filter narrow band signals with random frequency hopping spread spectrum. The proposed method is based on three steps. Firstly, the detection of Signal Frequency Hopping (SFH) using the Fast Fourier Transform (FFT), an algorithm to estimate the Dominant Frequency Value (DFV) is developed, it is necessary for better refining the original detection, in particular, with modulated signals. Secondly, the estimated frequency value is scaled and used with a Numerically Controlled Oscillator (NCO) in order shift the interest channel to baseband. Thirdly, the transposed channel in base band is selected using low pass Finite Impulse Response (FIR) filters. Whereas, the multi rate filtering techniques guarantee the high selectivity and low orders of these FIR filters. Each of the following stages is described in detail later in this paper, synthesizing these steps leads to the proposed solution, that is validated by using GSM signals. The algorithms are implemented in Field Programmable Gate Array (FPGA) Altera Cyclone III famil

Characterization of Radio Frequency Echo using frequency sweeping and power analysis

International audienceCoupling between repeater's antennas, called Radio Frequency Echo (RFE) deteriorates signal quality and compromises system stability. If the channel insulation is insufficient, the power in the closed-loop raises with time according to the gain margin value. Multiple methods of echo cancellation exists. Generally, these techniques are based on correlation calculation and adaptive filtering. However, their efficiency and algorithm's convergence speed are calling into question under signal's modulation and real-time constraints, specially with narrow band signals having frequency hopping as GSM or TETRA. This paper describes a real time method of RFE detection and estimation independently of the nature of the incoming signal. It is based on frequency sweeping and analysis of power ripples, and it can be implemented on FPGA for real-time purpose. It gives an accurate estimation of corresponding gain margin and loop delay. Index Terms—Radio frequency echo, gain margin, narrow band, frequency hopping

Étude et optimisation d'un système d'annulation d'écho pour répéteur de radiocommunication

International audienceLe phénomène d'écho en radio-fréquence (RF) se produit au sein d'un répéteur iso-fréquence (IF) lorsque l'isolation entre l'antenne d'émission et l'antenne de réception est insuffisante. L'objectif de ces travaux est de trouver un système d'identification et d'annulation d'écho, en se basant sur le traitement avancé du signal. Cette solution doit être implémenatable matériellement, sur un cir- cuit programmable type FPGA, l'objectif est de travailler en temps réel. La vitesse de convergence des algorithmes, leurs coûts en terme de ressources matérielles et leurs robustesses aux bruits font partie de l'optimisation recherchée. Cette solution doit être utilisable pour divers types de signaux comme le GSM, UMTS, TETRA, etc